Lung Cancer - Non Small CellStage I NSCLCNCT06737367
Integrating Machine Learning for Prognostic Prediction in Stage I NSCLC by CT Images and Pathological Factors
An observational study of Lung Cancer - Non Small Cell, run by Jinling Hospital, China at 1 site in China.
Trial summary
The investigators retrospectively collected the participants with stage I non-small cell lung cancer (NSCLC) patients resected between January 2010 to December 2020 for training and internal validation. The Clinical data, preoperative clinical information, laboratory results and CT images were collected. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Lung Cancer - Non Small Cell
- What is being tested?
- CT radiomic analysis
- How many people
- 800 participants
- Where
- 1 siteChina
- Study dates
- 1 Sep 2023to 11 Nov 2024
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Jinling Hospital, China
Who may be able to join
- patients with stage I NSCLC (ninth AJCC edition) who underwent curative R0 resections between January 2010 and December 2020 -
Who cannot join
- absence of enhanced CT
- history of lung cancer or synchronous lung cancers
- follow-up records ≤3 Months
- carcinoma in situ (CIS) or minimally invasive NSCLC
- death within 30 days of surgery
- no pathological slides or reports
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Integrating Machine Learning for Prognostic Prediction in Stage I NSCLC: a Multicenter Analysis
The investigators retrospectively collected the participants with stage I non-small cell lung cancer (NSCLC) patients resected between January 2010 to December 2020 for training and internal validation. The Clinical data, preoperative clinical information, laboratory results and CT images were collected. The investigators also collected the disease-free survival time. On the Deepwise multi-modal research platform, the images were semi-automatically segmented and expanded outward by 3mm to obtain the peritumor tissue. PyRadiomics was used to extract the radiomic features. LASSOcox and rsf were used to select the features. we developed a machine learning-based integrative prognostic model that utilizes radiomic and pathological variables as input using LOOCV framework. And it was further tested on the internal and external cohorts. Discrimination was assessed by using the C-index and area under the receiver operating characteristic curve (AUC), IBS, DCA.
- Conditions
- Lung Cancer - Non Small Cell
- Being tested
- CT radiomic analysis
- Keywords
- NSCLC, ML, DFS
- Medical subject headings
- Carcinoma, Non-Small-Cell Lung
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
CT radiomic analysisOther
Radiomic features of tumor and peritumor tissue
| Study group | Role | What they receive |
|---|---|---|
| training set | Not described Receives: Other: CT radiomic analysis | |
| external test set | Not described Receives: Other: CT radiomic analysis |
What is being measured
The primary outcome is the main question the study is designed to answer.
DFS（Disease-free survival）
DFS was defined as the duration from the date of primary surgery to the first occurrence of recurrence or death from any cause.
Measured: Record from the date of surgery to the date of recurrence or death from any cause, whichever comes first, and assess up to a maximum of 5 years.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted17 Dec 2024
- Study start1 Sep 2023
- Primary completion20 Sep 2024
- Study completion11 Nov 2024
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Lung Cancer - Non Small CellStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Retrospective
- Enrolment
- 800 participants (actual)
Sponsor and investigators
- Lead sponsor
- Jinling Hospital, China
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Guangming Lu, Jinling Hospital, China
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06737367
- Sponsor's protocol ID
- 2023DZKY-089-01
- Acronym
- Stage I NSCLC
- Status last verified
- Dec 2024
- First submitted
- 11 Dec 2024
- Last updated
- 19 Dec 2024
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 19 Dec 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Integrating Machine Learning for Prognostic Prediction in Stage I NSCLC: a Multicenter Analysis
- ClinicalTrials.gov ID
- NCT06737367
- Acronym / sponsor ID
- Stage I NSCLC / 2023DZKY-089-01
- Conditions
- Lung Cancer - Non Small Cell
- Keywords
- NSCLC, ML, DFS
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 800 participants (actual)
- Lead sponsor
- Jinling Hospital, ChinaUniversity, hospital or other
- Study start
- 1 Sep 2023 (actual)
- Primary completion
- 20 Sep 2024 (actual)
- Study completion
- 11 Nov 2024 (actual)
- First posted
- 17 Dec 2024 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The investigators retrospectively collected the participants with stage I non-small cell lung cancer (NSCLC) patients resected between January 2010 to December 2020 for training and internal validation. The Clinical data, preoperative clinical information, laboratory results and CT images were collected. The investigators also collected the disease-free survival time. On the Deepwise multi-modal research platform, the images were semi-automatically segmented and expanded outward by 3mm to obtain the peritumor tissue. PyRadiomics was used to extract the radiomic features. LASSOcox and rsf were used to select the features. we developed a machine learning-based integrative prognostic model that utilizes radiomic and pathological variables as input using LOOCV framework. And it was further tested on the internal and external cohorts. Discrimination was assessed by using the C-index and area under the receiver operating characteristic curve (AUC), IBS, DCA.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| training set | – | Other: CT radiomic analysis |
| external test set | – | Other: CT radiomic analysis |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Jinling Hospital, China
Key inclusion criteria (1 listed)
- patients with stage I NSCLC (ninth AJCC edition) who underwent curative R0 resections between January 2010 and December 2020 -
Key exclusion criteria (6 listed)
- absence of enhanced CT
- history of lung cancer or synchronous lung cancers
- follow-up records ≤3 Months
- carcinoma in situ (CIS) or minimally invasive NSCLC
- death within 30 days of surgery
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| CT radiomic analysisRadiomic features of tumor and peritumor tissue | Other | external test set, training set |
Primary outcome
DFS（Disease-free survival）
Time frame: Record from the date of surgery to the date of recurrence or death from any cause, whichever comes first, and assess up to a maximum of 5 years.
DFS was defined as the duration from the date of primary surgery to the first occurrence of recurrence or death from any cause.
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 19 Dec 2024.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Lung Cancer - Non Small Cell, run by Jinling Hospital, China at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 1 inclusion and 6 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 19 Dec 2024. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
DFS（Disease-free survival） (time frame: Record from the date of surgery to the date of recurrence or death from any cause, whichever comes first, and assess up to a maximum of 5 years.). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 19 Dec 2024; AzTrials last refreshed its copy on 31 Oct 2026.